Composable building blocks to build Llama Apps https://llama-stack.readthedocs.io
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Ashwin Bharambe 01a25d9744
feat(server): add attribute based access control for resources (#1703)
This PR introduces a way to implement Attribute Based Access Control
(ABAC) for the Llama Stack server.

The rough design is:
- https://github.com/meta-llama/llama-stack/pull/1626 added a way for
the Llama Stack server to query an authenticator
- We build upon that and expect "access attributes" as part of the
response. These attributes indicate the scopes available for the
request.
- We use these attributes to perform access control for registered
resources as well as for constructing the default access control
policies for newly created resources.
- By default, if you support authentication but don't return access
attributes, we will add a unique namespace pointing to the API_KEY. That
way, all resources by default will be scoped to API_KEYs.

An important aspect of this design is that Llama Stack stays out of the
business of credential management or the CRUD for attributes. How you
manage your namespaces or projects is entirely up to you. The design
only implements access control checks for the metadata / book-keeping
information that the Stack tracks.

### Limitations

- Currently, read vs. write vs. admin permissions aren't made explicit,
but this can be easily extended by adding appropriate attributes to the
`AccessAttributes` data structure.
- This design does not apply to agent instances since they are not
considered resources the Stack knows about. Agent instances are
completely within the scope of the Agents API provider.

### Test Plan

Added unit tests, existing integration tests
2025-03-19 21:28:52 -07:00
.github feat: [New Eval Benchamark] IfEval (#1708) 2025-03-19 16:39:59 -07:00
distributions chore: deprecate /v1/inspect/providers (#1678) 2025-03-19 20:27:06 -07:00
docs chore: deprecate /v1/inspect/providers (#1678) 2025-03-19 20:27:06 -07:00
llama_stack feat(server): add attribute based access control for resources (#1703) 2025-03-19 21:28:52 -07:00
rfcs chore: remove straggler references to llama-models (#1345) 2025-03-01 14:26:03 -08:00
scripts feat(server): add attribute based access control for resources (#1703) 2025-03-19 21:28:52 -07:00
tests feat(server): add attribute based access control for resources (#1703) 2025-03-19 21:28:52 -07:00
.gitignore build: remove .python-version (#1513) 2025-03-12 20:08:24 -07:00
.pre-commit-config.yaml chore: consolidate scripts under ./scripts directory (#1646) 2025-03-17 17:56:30 -04:00
.readthedocs.yaml first version of readthedocs (#278) 2024-10-22 10:15:58 +05:30
CHANGELOG.md docs: Add v0.1.6 release notes to changelog (#1506) 2025-03-08 16:20:08 -08:00
CODE_OF_CONDUCT.md Initial commit 2024-07-23 08:32:33 -07:00
CONTRIBUTING.md docs: fix broken test path in CONTRIBUTING.md (#1679) 2025-03-18 13:39:46 -07:00
LICENSE Update LICENSE (#47) 2024-08-29 07:39:50 -07:00
MANIFEST.in build: include .md (#1482) 2025-03-07 12:10:52 -08:00
pyproject.toml chore: fix mypy violations in post_training modules (#1548) 2025-03-18 14:58:16 -07:00
README.md docs: remove redundant installation instructions (#1138) 2025-03-18 14:52:21 -07:00
requirements.txt ci: Bump version to 0.1.7 2025-03-14 15:21:26 -07:00
SECURITY.md Create SECURITY.md 2024-10-08 13:30:40 -04:00
uv.lock feat: Qdrant inline provider (#1273) 2025-03-18 14:04:21 -07:00

Llama Stack

PyPI version PyPI - Downloads License Discord Unit Tests Integration Tests

Quick Start | Documentation | Colab Notebook

Llama Stack standardizes the core building blocks that simplify AI application development. It codifies best practices across the Llama ecosystem. More specifically, it provides

  • Unified API layer for Inference, RAG, Agents, Tools, Safety, Evals, and Telemetry.
  • Plugin architecture to support the rich ecosystem of different API implementations in various environments, including local development, on-premises, cloud, and mobile.
  • Prepackaged verified distributions which offer a one-stop solution for developers to get started quickly and reliably in any environment.
  • Multiple developer interfaces like CLI and SDKs for Python, Typescript, iOS, and Android.
  • Standalone applications as examples for how to build production-grade AI applications with Llama Stack.
Llama Stack

Llama Stack Benefits

  • Flexible Options: Developers can choose their preferred infrastructure without changing APIs and enjoy flexible deployment choices.
  • Consistent Experience: With its unified APIs, Llama Stack makes it easier to build, test, and deploy AI applications with consistent application behavior.
  • Robust Ecosystem: Llama Stack is already integrated with distribution partners (cloud providers, hardware vendors, and AI-focused companies) that offer tailored infrastructure, software, and services for deploying Llama models.

By reducing friction and complexity, Llama Stack empowers developers to focus on what they do best: building transformative generative AI applications.

API Providers

Here is a list of the various API providers and available distributions that can help developers get started easily with Llama Stack.

API Provider Builder Environments Agents Inference Memory Safety Telemetry
Meta Reference Single Node
SambaNova Hosted
Cerebras Hosted
Fireworks Hosted
AWS Bedrock Hosted
Together Hosted
Groq Hosted
Ollama Single Node
TGI Hosted and Single Node
NVIDIA NIM Hosted and Single Node
Chroma Single Node
PG Vector Single Node
PyTorch ExecuTorch On-device iOS
vLLM Hosted and Single Node
OpenAI Hosted
Anthropic Hosted
Gemini Hosted

Distributions

A Llama Stack Distribution (or "distro") is a pre-configured bundle of provider implementations for each API component. Distributions make it easy to get started with a specific deployment scenario - you can begin with a local development setup (eg. ollama) and seamlessly transition to production (eg. Fireworks) without changing your application code. Here are some of the distributions we support:

Distribution Llama Stack Docker Start This Distribution
Meta Reference llamastack/distribution-meta-reference-gpu Guide
Meta Reference Quantized llamastack/distribution-meta-reference-quantized-gpu Guide
SambaNova llamastack/distribution-sambanova Guide
Cerebras llamastack/distribution-cerebras Guide
Ollama llamastack/distribution-ollama Guide
TGI llamastack/distribution-tgi Guide
Together llamastack/distribution-together Guide
Fireworks llamastack/distribution-fireworks Guide
vLLM llamastack/distribution-remote-vllm Guide

Documentation

Please checkout our Documentation page for more details.

Llama Stack Client SDKs

Language Client SDK Package
Python llama-stack-client-python PyPI version
Swift llama-stack-client-swift Swift Package Index
Typescript llama-stack-client-typescript NPM version
Kotlin llama-stack-client-kotlin Maven version

Check out our client SDKs for connecting to a Llama Stack server in your preferred language, you can choose from python, typescript, swift, and kotlin programming languages to quickly build your applications.

You can find more example scripts with client SDKs to talk with the Llama Stack server in our llama-stack-apps repo.